The American Joint Committee on Cancer has recently revised the tumor-node-metastasis (TNM) staging system on thyroid cancer, which illustrated that the cut-off age for predicting mortality has elevated from 45 to 55 years old. We aimed to investigate the inflammation index based on hematological parameters to predict the clinical characteristics of elderly papillary thyroid cancer (PTC) patients with an inferior prognosis. We retrospectively analyzed 558 patients newly diagnosed with PTC from January 2013 to December 2017, and 82 out of the 558 patients were over 55 years old. Receiver operating characteristic (ROC) study and univariate and multivariate logistic analysis was conducted to evaluate the diagnostic value of these preoperative inflammation indexes in PTC patients ≥ 55 years of age. Elevated neutrophils were prognostic of bilaterality (area under the ROC curve (AUC) = 0.673, p = 0.023) and lymph node metastasis (AUC = 0.649, p = 0·020). Decreased mean platelet volume (MPV) and platelet distribution width (PDW) were prognostic of coexistence with Hashimoto’s thyroiditis (AUC = 0.736, p = 0.016; AUC = 0.721, p = 0.024). Elevated lymphocyte and lymphocyte-to-monocyte ratio (LMR) were prognostic of advanced TNM stage (AUC = 0.691, p = 0.029; AUC = 0.680, p = 0.040). Meanwhile, the logistic regression model further revealed that LMR ≥ 5.45 was an independent risk factor for the advanced TNM stage (odds ratio (OR) = 7.306, p = 0.036). The preoperative neutrophils, lymphocytes, MPV, PDW, LMR were all prognostic. More importantly, the increased in LMR independently contributed to the advanced TNM stage of PTC patients ≥ 55 years.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic dysfunction-associated steatohepatitis (MASH) is a critical link leading to cirrhosis and hepatocellular carcinoma. Yet the responsible cellular programs remain unclear. We integrated public single-cell, spatial, and bulk transcriptomic datasets to map microenvironmental remodeling and regulatory networks during MASLD-MASH progression. Among the seven major liver cell types identified, monocytes/macrophages and hepatic stellate cells (HSCs) were significantly enriched and demonstrated spatial co-localization within the context of MASH. We identified a DTNA+distinct macrophage subpopulation that was specifically enriched in MASH. This subpopulation exhibited characteristics consistent with M2 polarization, hypoxia, and enhanced inflammatory signaling. Pseudotime trajectory analysis revealed that this state represents a differentiation pathway originating from Kupffer cells to the DTNA+ state. RUNX2 emerged as the key transcriptional regulator. Cell communication analysis demonstrated that DTNA+ macrophages potentially interact with activated HSCs via the RUNX2-PLG-PARD3 axis, contributing to the exacerbation of liver fibrosis. Finally, ensemble machine learning models (mean AUC = 0.839), identified DTNA as the optimal predictive biomarker for distinguishing MASLD from MASH. This study highlight DTNA+ macrophages and the RUNX2–PLG–PARD3 axis as candidate mechanisms and targets for non-invasive diagnosis and therapy in MASH.

Background/Objectives: The role of glycogen metabolism in diabetic kidney disease (DKD) remains unclear. This study investigated the therapeutic potential of asiatic acid (AA) on glycogen metabolism in DKD and its underlying mechanisms. Methods: A DKD mouse model was established using a high-fat diet and streptozotocin, followed by AA treatment for 8 weeks. Network pharmacology and molecular docking identified STBD1 as a potential target of AA, and its overexpression in mice was performed. Results: AA reduced blood glucose levels and the urinary albumin-to-creatinine ratio (UACR) and downregulated TGFβ-1, KIM-1, and PDK4. Additionally, AA treatment reversed abnormal glycogen accumulation and restored STBD1 expression. Network pharmacology and molecular docking identified STBD1 as a potential target of AA, and its overexpression in mice demonstrated similar beneficial effects. Gene enrichment analysis revealed that STBD1 is involved in key metabolic pathways related to DKD. Conclusions: These findings suggest that AA alleviates renal damage in DKD, possibly through modulation of STBD1, highlighting its therapeutic potential and the critical role of STBD1 in renal glycophagy.